Source: Deep Learning on Medium
AI vs Machine Learning vs Deep Learning: What the differences?
There are many misconceptions of Artificial Intelligence(AI), Machine Learning, and Deep Learning. Many think they are the same. Yes, these three are related to each other, but still, they are not the same.
There is no fixed definition for AI, but here is a definition that will give you a context of what AI is. AI is an area of computer science that emphasizes the creation of intelligent machines that work and react like a human brain. Some of the activities computers with artificial intelligence are designed for include:
- Speech recognition
“AI is a ability of intellegent machine to function like a human brain”
Until today, we are not able to create or even close to establishing a proper AI, but we are on very fast progress to create one. One of the most advanced AI that we can create is Sophia. On of the reason we are not able to create proper AI is we don’t have a deep understanding of how our brain works. Because AI is so complex and covers a very broad aspect of expertise, scientist and researcher develop many AI subfields of study, two of them are Machine Learning and Deep Learning.
Machine learning is a subset of AI that enables systems to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it to learn for themselves.
Before we go deeper into machine learning, we should understand data mining. Data mining is a technique of examining a large pre-existing database and extracting new information from that database. Machine learning does the same with data mining, in fact, machine learning is a type of data mining technique.
“Machine Learning is a subsets of AI that enables systems to learn from that data, use it to learn for themselves then apply what they have learned to make an informed decision”
Nowadays many big companies use machine learning to give their customers a better customer experience. Amazon uses machine learning to give better product choice recommendations to there costumers based on their preferences, while Netflix uses machine learning to give better suggestions to their users of the Tv series or movie or shows that they would like to watch.
Deep Learning is a subfield of machine learning concerned with algorithms inspired by the structure and function of the brain called artificial neural networks. Deep Learning is machine learning and functions in the same way but it has different capabilities.
The main difference between deep and machine learning is, machine learning models become better progressively but the model still needs some guidance. If a machine learning model returns an inaccurate prediction then the programmer needs to fix that problem explicitly but in the case of deep learning, the model does it by himself.
Andrew Ng founder of Coursera and Chief Scientist at Baidu Research formally founded Google Brain that eventually resulted in the productization of deep learning technologies across a large number of Google services. He has spoken and written a lot about deep learning, and I think he had defined fixed definitions of what Deep learning is. In early talks on deep learning, Andrew described deep learning in the context of traditional artificial neural networks. In the 2013 talk titled “Deep Learning, Self-Taught Learning and Unsupervised Feature Learning” he described the idea of deep learning as:
Using brain simulations, hope to:
- Make learning algorithms much better and easier to use.
- Make revolutionary advances in machine learning and AI.
I believe this is our best shot at progress towards real AI
“Deep Learning actually is machine learning and functions in the same way but it has different capabilities, because deep learning focus to mimic function of the brain called artificial neural networks”